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Record W2070318815 · doi:10.1680/coma.11.00064

Effect of limestone addition on early-age properties of ultra high-performance concrete

2012· article· en· W2070318815 on OpenAlexaff
Jessica Camiletti, Ahmed Soliman, Moncef L. Nehdi

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Construction Materials · 2012
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsWestern University
Fundersnot available
KeywordsCementMaterials scienceMicrostructureInertFiller (materials)Composite materialEnvironmentally friendlyCalcium carbonateCompressive strengthChemistry

Abstract

fetched live from OpenAlex

In the present study, the effects of using limestone as partial replacement for cement on the early-age properties of ultra high-performance concrete cured at simulated cold and normal field conditions were investigated. Different particle sizes of limestone, ranging from nano (15–40 nm) up to 12 µm, were added at rates of 0, 5, 10 and 15% as partial volume replacement for cement. The results indicate that in very low water/cement ratio concrete mixtures, the incorporated micro-sized limestone acts mainly as an inert filler material, creating a denser microstructure and increasing the effective water/cement ratio. Although the mixtures incorporating micro-sized limestone exhibited mechanical properties that were comparable to or weaker than those of mixtures incorporating nano-sized calcium carbonate, they had similar or higher mechanical properties than those of the control mixture without limestone. Thus, environmentally friendly concrete can be produced using micro-limestone, by reducing the cement factor of ultra high-performance concrete while enhancing the mechanical properties

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.201
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2012
Admission routes1
Has abstractyes

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